The weights of the encoder and the decoder are updated using Adam whereas those of the discriminator are updated using SGD. It has been found out empirically by [1]} that annealing \(L_{KL}\)  yields better results by making Adam optimizer to focus on minimizing the reconstruction loss term, which is tougher than optimizing KL Divergence loss. Therefore the modified objective is given as:
\(Loss = L_R + w_{KL} \eta _{t} L_{KL} + L_{adv}^G, \quad \text{where} \hspace{4.0pt}\eta _{t} = 1 - (1 - \eta _{min})R^{t}\) 
